# Pre-registered, publicly scored AI ranking of repurposing candidates for cancer

Source: https://onco.cc/ideas/idea-reg-preregistered-ai-repurposing-scoring/  
OnCo record `idea-reg-preregistered-ai-repurposing-scoring` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

AI systems claim to find new uses for old drugs, but their predictions are rarely tested fairly. Publish their cancer predictions in advance and score them against trial results.

## Summary

Knowledge-graph and language-model approaches to repurposing (Every Cure, funded by ARPA-H; academic systems such as those built on Hetionet and Open Targets) generate ranked lists of drug-disease pairs, but their forward-looking accuracy in oncology is unknown because predictions are published selectively after the fact. The proposal is a public benchmark: each participating system deposits time-stamped ranked predictions for defined cancer indications; a neutral body scores them annually against subsequent randomised trial results and target trial emulations, and the repurposing fund preferentially trials candidates on which independent systems agree.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: Candidates ranked highly by at least two independent pre-registered systems have a positive-trial rate at least twice that of candidates selected by conventional literature review.
- Rationale: Prospective, pre-registered evaluation is the only way to know whether these tools add value beyond the literature they were trained on; if they do, they should direct scarce trial funding, and if they do not, that should be known.
- Proposed test: Launch the benchmark with three systems and a five-year horizon; compare the fate of top-ranked candidates with a matched set chosen by expert panel.
- Maturity: early-clinical
- Actor: data

## Sources

- Bottleneck evidence (No incentive to repurpose cheap drugs): Pantziarka et al., The Repurposing Drugs in Oncology (ReDO) Project (ecancer 2014): https://doi.org/10.3332/ecancer.2014.442

## Connected records

- collections: [DrugBank & ChEMBL](https://onco.cc/collections/drugbank-chembl/), [Open Targets Platform](https://onco.cc/collections/open-targets/)
- bottlenecks: [AI that is built but not validated or deployed](https://onco.cc/bottlenecks/b-ai-validation/), [No incentive to repurpose cheap drugs](https://onco.cc/bottlenecks/b-generic-repurposing/)
- key papers: [The Repurposing Drugs in Oncology (ReDO) Project](https://onco.cc/key-papers/paper-pantziarka-ecancermedicalscience/)

---
JSON: https://onco.cc/api/v1/entities/idea-reg-preregistered-ai-repurposing-scoring.json